Finally, these materials demonstrated good antimicrobial activity against S. aureus while retaining good cell viabilities (above 90%) for fibroblasts BALB/3T3.The modification of medical devices is an area that has attracted a lot of attention in recent years; particularly, those developments which search to modify existing devices to render them antimicrobial. Most of these modifications involve at least two stages  which are both time-consuming and complicate synthetic procedures; therefore, as an improvement, this project sought to produce antimicrobial silicone (PDMS) in a single step. Using gamma radiation as both an energy source for polymerization initiation and as a source of reducing agents in solution, PDMS was simultaneously grafted with acrylic acid and ethylene glycol dimethacrylate (AAc:EGDMA) while producing antimicrobial silver nanoparticles (AgNPs) onto the surface of the material. To obtain reproducible materials, experimental variables such as the effect of the dose, the intensity of radiation, and the concentration of the silver salt were evaluated, finding the optimal reaction conditions to obtain materials with valuable properties. The characterization of the material was performed using electronic microscopy and spectroscopic techniques such as  Silicone elastomers  are polymers which possess properties that are very important for the development of devices on medicine ,2,3. For2 surfaces with a mixture of ampicillin and silver nanoparticles (AgNPs) to stop the propagation of Gram-positive S. aureus ) was varied instead of time to control this variable for the following experiments. Two different radiation intensities were tested, and when I was decreased from 10 to 5 kGy h3 were tested at I = ~5 kGy h−1, to check the effect of exposure to radiation in the formation of AgNPs with different shapes or sizes. Concentrations of 5, 10, and 50 mM of silver nitrate were evaluated. After exposure, SF developed different colors depending on the intensity of radiation (see Three concentrations of AgNOtion see a. The tySilver nanoparticles have a surface plasmon resonance (SPR) depending on the shape and size of the particle which can be detected by UV-Visible Spectroscopic analysis. The presence of the nanoparticles was confirmed in the different films by that technique. The spectra in 3 and increased radiation exposure (I = ~5 kGy) This can be explained with the continuous reduction reactions happening while the radiation where silver clusters are easier to form.The spherical nanoparticles yielded a SPR peak at 435 nm, similar to the value previously reported for spherical and quasi-spherical AgNPs with sizes below 20 nm . It is nDue to the thickness of the films, images from transmission microscopy could not be obtained; however, scanning electron microscopy (SEM) was successful. The obtained micrographies show the morphologies of the films’ surfaces before a and aftAdditionally, the energy-dispersive X-ray spectrometry (EDX) information confirmed the presence of silver and the AAc:EDGMA graft on the surface. Films with a lower concentration of silver b showed To test for the stability of the materials, the films were exposed to atmospheric oxygen and water for 12 months and monitored periodically. Both tests were performed in the absence of light. The films remained without color changes for 12 months, suggesting the absence of oxidation reactions which would have darkened the samples. FTIR-ATR and UV-Vis spectra were recorded after 6 months and very similar spectral data was obtained see . In an ag-(AAc-co-EGDMA) + Ag (10 mM) (orange) was used for preliminary antimicrobial analyses against Gram-positive and Gram-negative bacteria. The results were compared between this sample, the film without silver and pristine silicone. As seen in g-(AAc-co-EGDMA) + Ag (10 mM) for the three bacteria after 24 h according to absorbance measurements.The film: SF-g-(AAc-co-EGDMA) + Ag (10 mM) showed better inhibition for S. aureus in which the bacterial growth decreases up to a value of ~40% of cells (in comparison to 100% for other samples) after 24 h. For E. coli, the inhibition was less significant, as well as for P. aeruginosa, the inhibiting effect was less dramatic; however, slight growth inhibition is still observed, which is common for silver modified materials. To examine if these differences are significant, a one-way ANOVA difference of means test with a confidence level of p = 0.01 was performed  and Gram-positive S. aureus. Despite what previous reports suggest, the antibacterial effect was dramatic for S. aureus than E. coli and P. aeruginosa, even though S. aureus is a Gram-positive bacteria. The higher bactericidal effect against S. aureus can be attributed to the antimicrobial mechanism is by direct contact between the cell wall and the AgNP surface, as it has been reported for Gram-positive S. epidermidis in glass surfaces modified with AgNPs which showed antibacterial effect by cell/surface contact [+ produced by oxidation of AgNPs [ contact ,67. For of AgNPs . SomethiS. aureus, the performance of the SF prepared with different concentrations of silver was tested. The bacterial growth inhibition was evaluated as a function of time  and could be confused with bacterial growth on absorbance measurements. This effect is not seen in materials with lower concentrations of silver because the oxidation and aggregation are more probable in materials with more concentrations of silver.As it may be noted, the inhibition of the film prepared with a concentration of 50 mM AgNOThe antibacterial effect of the AgNPs depends on the particle size; small-diameter particles have a larger area and thus more contact with the bacteria. For that reason, the films prepared with 10 mM of silver nitrate with an excess of small spherical particles showed the same effect as the films containing more Ag (50 mM), because the effect is due to the size of the nanoparticles rather than to the concentration.Cell viability was evaluated in small volumes of growth medium in direct contact with BALB/3T3 (mouse). As shown in −3 and a thickness of 1 mm were purchased from Good-fellow . Silver nitrate (99.9%), ethylene glycol dimethacrylate, and acrylic acid were acquired from Sigma-Aldrich Co. . All the monomers were purified under vacuum distillation before used. Deionized water and ethanol  were obtained from Baker Mexico and were used without further purification.Silicone films (1 × 4 cm) with a density ranging from 1.1 to 1.5 g cmg-(AAc-co-EGDMA)). The monomer concentrations tested were 10 and 20% (v/v) in EtOH:H2O (1:1) mixture as a solvent.As preliminary experiments, silicone films (SF) were introduced in an ampoule containing 8 mL of an AAc:EGDMA mixture in 3:1 and 5:1 ratios (SF-g-(AAc-co-EGDMA) + Ag), different solutions with a concentration of silver nitrate were used  the AgNO3 was dissolved in the monomer/EtOH:H2O solutions. Monomer concentration was fixed at 20% v/v in a ratio 3:1 (AAc:EGDMA). The ampoules were deoxygenated by displacing oxygen with Argon for 20 min subsequently the ampoules were sealed and later exposed to variable doses of 60Co γ-radiation (I = ~5 and ~10 kGy h−1) using a Gammabeam 651PT available in the Institute of Nuclear Sciences (ICN) at the National Autonomous University of Mexico (UNAM) to initiate the polymerization reaction. After exposing the films to radiation, all the modified SF were washed in different solvents to remove the occluded solvent, AgNO3, monomer, and copolymer residues. Finally, the samples were dried under vacuum (−80 kPa) at 40 °C and weighed.In silicone films with silver immobilization (SF-m0) and grafted-PDMS (gm), the general formula is shown in Equation (1):The grafting yield (GY) was calculated from the weight difference between pristine PDMS  was calculated for all measurements.To check for a successful modification of the materials the Fourier Transform Infrared Spectroscopy Attenuated Total Reflectance Spectroscopy (FTIR ATR) using a Perkin-Elmer Spectrum 100 spectrometer . All the materials were dried under a vacuum before the measurements. The characterization of the surfaces was made using UV-VIS spectroscopy using an Ocean Optics HR4000CG-UV-NIR, and the Scanning Electron Microscopy (SEM) in a JEOL JSM 5900 LV with graphite recovering at 20 kV and energy-dispersive X-ray spectrometry (EDX). Since both FTIR ATR measurements are performed on the solid state, sample preparation only consisted of the aforementioned vacuum dry.The equilibrium water content (EWC%) was measured in deionized water for 48 h each, the excess of water was removed using filter paper and then the films were weighted. The swelling degree (SD) was calculated using Equation (2):gm and sm represent the mass of the grafted and the swollen film, respectively. All the experiments were repeated thrice, and the standard error of the mean (Err) was calculated for all measurements.For contact angle a Kruss DSA 100 drop shape analyzer  was used, the angle was recorded at 5 min after deionized water droplet had been deposited into the dry samples. All the experiments were made thrice.g-(AAc-co-EGDMA), SF-g-(AAc-co-EGDMA) + Ag (1 cm2 and 100 mg), were placed in tubes containing Staphylococcus aureus , Escherichia coli , or Pseudomonas aeruginosa  in Muller–Hinton agar at a concentration of approximately 1.5 × 108 CFU mL−1 (0.5 McFarland) and then incubated at 37 °C for 3, 6, 12, 24, and 48 h. Control cultures with and without bacteria were also prepared with this method. To quantify bacterial growth, light absorption by the culture media was measured in a UV–Vis spectrophotometer at wavelengths ranging from 450 to 800 nm. Absorbance at 600 nm was used to compare bacterial growth in all the systems as stated in the literature [p = 0.01) was conducted to evaluate the statistical significance of the results at 24 h. The details of the ANOVA test are presented in the Small pieces of SF, SF-terature . All bacPost-hoc (Tukey test) tests allowed to determine which of the samples had indeed different ability to stop growth inhibition for each bacteria.w/v), and gentamicin (10 µg/mL). Experiments were performed in 96 well plates with 50,000 cells mL−1 for 12 h incubated in a humidified atmosphere of 5% CO2 at 37 °C. SF-g-(AAc-co-EGDMA), and SF-g-(AAc-co-EGDMA) + Ag films (0.25 × 0.20 cm), were submerged in the cell media for 24 h in culture standard conditions. After this time, the films were removed and cell viability was determined using a MTT kit . All experiments were performed thrice and compared with cells without films as a negative control. Finally, absorbances were obtained using a Multiskan FC, Thermo Scientific spectrophotometer at 620 nm. Cytocompatibility (%) is calculated as follows:The cytocompatibility tests were performed using a murine embryonic fibroblast cell line BALB/3T3 . The fibroblast cell line was cultured in Dulbecco’s modified Eagle’s medium (DMEM) with FBS 10% , penicillin-streptomycin (1% p = 0.01) was conducted to evaluate the statistical significance of the results at 24 h. The details of the ANOVA test are presented in the All cytocompatibility tests were performed three times and a one-way ANOVA difference of means test (0: % Cell viabilitySF = % Cell viabilityco-EDGMA)SF-g-(AAc- = % Cell viabilityco-EDGMA) + Ag (10 mM)SF-g-(AAc- = % Cell viabilityco-EDGMA) + Ag (20 mM)SF-g-(AAc- = % Cell viabilityco-EDGMA) + Ag (50 mM)SF-g-(AAc-.Ha: % Cell viabilitySF ≠ % Cell viabilityco-EDGMA)SF-g-(AAc- ≠ % Cell viabilityco-EDGMA) + Ag (10 mM)SF-g-(AAc- ≠ % Cell viabilityco-EDGMA) + Ag (20 mM)SF-g-(AAc- ≠ % Cell viabilityco-EDGMA) + Ag (50 mM)SF-g-(AAc- post-hoc (Tukey test) tests allowed to determine which of the samples had differences in their cytocompatibility.HThe simultaneous polymer grafting and silver reduction using gamma radiation were successfully reached in ethanol:water solution. With the analysis of the obtained materials, it was possible to determine the necessary conditions to obtain reproducible grafts while also determining the synthetic conditions that allow for AgNPs to form within the polymer grafts. The presence of silver on the SF was verified by EDX elemental analysis, UV-vis determination of plasmon resonance, and SEM microscopy. As suggested through the change of color of the films from clear to orange, the formation of spherical or quasi-spherical AgNPs.g-(AAc-co-EGDMA) + Ag showed good antimicrobial activity against S. aureus and some antimicrobial activity of E. coli and P. aeruginosa while maintaining and a cytocompatibility (above 90%) as long as the concentration of silver was 10 mM or lower.The modified films SF-


Nivolumab, an immune checkpoint inhibitor, is beneficial to patients with platinum-refractory recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC). However, platinum-sensitive R/M-HNSCC has not yet been studied. Hence, in this prospective study, we evaluated the efficacy and safety of nivolumab in patients with platinum-sensitive R/M-HNSCC. This prospective single-arm study was conducted in a single institution in Japan. Patients with platinum-sensitive R/M-HNSCC (defined as head and neck cancer that recurred or metastasized at least 6 months after platinum-based chemotherapy or chemoradiotherapy) were enrolled. The primary endpoint was overall survival (OS). The secondary endpoints were progression-free survival (PFS), overall response rate (ORR), immune-related adverse events (irAEs), and quality of life (QOL). This study was registered at the University Hospital Medical Information Network Clinical Trials Registry (UMIN000031324). Twenty-two patients with platinum-sensitive R/M-HNSCC were enrolled. The median OS was 17.4 months, and the 1-year OS rate was 73%. The median PFS was 9.6 months, 1-year PFS rate was 48%, and ORR was 36%. Sixteen irAEs were recorded in 12 patients; however, no grade 4 or 5 irAEs were observed. The QOL assessments revealed that nivolumab did not decrease the QOL of patients. Nivolumab is effective against platinum-sensitive R/M-HNSCC with acceptable safety. In 2016, an international phase III trial (CheckMate-141) revealed that, compared with the standard-of-care, nivolumab (an immune checkpoint inhibitor) prolonged the OS of patients with platinum-refractory R/M-HNSCC. In the CheckMate-141 study, treatment with nivolumab led to a median OS of 7.5 months, median progression-free survival (PFS) of 2.04 months, and an overall response rate (ORR) of 13.3%4. Thus, the National Comprehensive Cancer Network (NCCN) Guidelines recommend nivolumab along with the EXTREME regimen as a category 1 treatment for patients with R/M-HNSCC with a history of platinum therapy6. Several studies, including a real-world retrospective study, have reported the efficacy of nivolumab, with median OS ranging from 8.7 to 13.0 months, median PFS ranging from 1.9 to 3.7 months, and ORR ranging from 13 to 30%10.The prognosis of patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC) is poor, with a median overall survival (OS) of less than 1 year12 has recently been applied to R/M-HNSCC13. Tumors are considered platinum-refractory if they recur or metastasize within 6 months after platinum-based chemotherapy or chemoradiotherapy. In contrast, tumors are considered platinum-sensitive if they recur or metastasize more than 6 months after platinum-based chemotherapy or chemoradiotherapy. Notably, CheckMate-141 only enrolled patients with platinum-refractory R/M-HNSCC, and no prospective study has been conducted on the efficacy and safety of nivolumab for platinum-sensitive R/M-HNSCC. The KEYNOTE 048 trial suggested that pembrolizumab, a programmed cell death protein 1 (PD-1) inhibitor, is effective against platinum-sensitive R/M-HNSCC14; pembrolizumab is also considered a category 1 therapy in the NCCN Guidelines5. Nivolumab, similar to pembrolizumab, is a PD-1 inhibitor, and it may be effective against platinum-sensitive R/M-HNSCC. The aim of this study was to prospectively evaluate the efficacy and safety of nivolumab in patients with platinum-sensitive R/M-HNSCC.The concept of platinum refractoriness initially used for treatment strategies for recurrent ovarian cancerN = 35), non-squamous cell carcinoma (N = 3), and age > 75 years (N = 1). Twenty-two patients who met the inclusion criteria were enrolled in this study. The data cutoff date was December 31, 2020. Detailed data of all patients are provided in the From February 16, 2018, to December 31, 2019, 61 patients with recurrent or metastatic head and neck cancer received at least one cycle of nivolumab. Among these, 39 patients were excluded owing to platinum resistance (N = 6) and maxillary sinus (N = 4). PD-L1 expression was < 1% in 5 patients, ≥ 1% in 16 patients, ≥ 20% in 12 patients, ≥ 40% in 8 patients, and unmeasured in 1 patient. Treatment modalities prior to nivolumab administration are presented in Table N = 3), definitive concurrent chemoradiotherapy (N = 13), postoperative chemoradiotherapy (N = 6), and systemic therapy for recurrence or metastasis . In addition, one patient underwent a duplicate platinum-containing regimen. Cetuximab was used prior to nivolumab treatment as a definitive concurrent radiotherapy (N = 1) and as a systemic therapy for countering the recurrence or metastasis of disease . The median period between the date of the last administration of platinum and the date of disease progression was 351  days, whereas the median period between the date of the last administration of platinum and the date of the first administration of nivolumab was 397  days. The median number of cycles of nivolumab administration was 9 .Table After data cutoff, the median follow-up period for all patients was 14.9 range, 3.1–33.7) months. The median OS was 17.4 months , and the 1-year OS rate was 73%  Fig. A,B. One .1–33.7 mN = 5), interstitial lung disease (N = 4), hypothyroidism (N = 4), hyperthyroidism (N = 1), and dermatitis (N = 2). The following grade 3 or higher irAEs occurred in four patients: liver dysfunction (N = 3) and hypothyroidism (N = 1).Table Functional scales  and global health status were assessed using the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ) Core 30 Module (QLQ-C30). Domain scales  were assessed using the EORTC QLQ Head and Neck Cancer Module (QLQ-H&N35). Detailed data regarding the quality of life (QOL) scores are provided in the The aim of this study was to determine the efficacy and safety of nivolumab in patients with platinum-sensitive R/M-HNSCC through a prospective study. The main outcomes of this study were the median OS of 17.4 months, median PFS of 9.6 months, ORR of 36%, and DCR of 68%. Although the number of patients in the study by primary site was too small to ensure the certainty of the results, there was no clear effect of the primary site on efficacy.3, it is evident that treatment with nivolumab improved the OS. To the best of our knowledge, this is the first prospective study to demonstrate the efficacy of nivolumab in patients with platinum-sensitive R/M-HNSCC only.Considering that the prognosis of patients with R/M-HNSCC is poor at less than 1 year12. In recurrent ovarian cancer, patients with platinum-sensitive cancer are more likely to respond to subsequent chemotherapy and have a better prognosis than those with platinum-resistant cancer12. For R/M-HNSCC, the effects of the EXTREME regimen on the OS of two groups of patients with R/M-HNSCC, namely patients with platinum-resistant and platinum-sensitive R/M-HNSCC, have been compared16. Sato et al. reported significantly better OS in patients with platinum-sensitive R/M-HNSCC than in those with platinum-resistant R/M-HNSCC 15. In contrast, Sano et al. showed that the OS of the non-platinum-refractory group was significantly higher than that of the platinum-refractory group 16. Hori et al. reported significantly better PFS in the non-platinum-refractory group than in the platinum-refractory group of nivolumab-treated patients with R/M-HNSCC 17. Although the results of Hori et al. cannot be directly compared with those of CheckMate-141 for platinum-refractory R/M-HNSCC or with those of retrospective studies, they provide further evidence of the benefits of nivolumab in patients with R/M-HNSCC17. Similar to patients with recurrent ovarian cancer, those with platinum-sensitive R/M-HNSCC may respond well to subsequent pharmacotherapy. In Japan, in addition to nivolumab, pembrolizumab is indicated for R/M-HNSCC. In 2019, Burtness et al. studied the efficacy of pembrolizumab as a primary treatment in patients with R/M-HNSCC without prior chemotherapy in the international phase III KEYNOTE-048 trial14. Among patients with PD-L1 combined positive scores ≥ 20, those treated with pembrolizumab alone exhibited significantly higher OS than the group administered the EXTREME regimen (cetuximab with chemotherapy group) . The NCCN Guidelines also recommend pembrolizumab as a category 1 treatment5. However, the KEYNOTE-048 trial included patients with R/M-HNSCC who underwent chemotherapy-free treatments; hence, the correlation between platinum sensitivity and pembrolizumab treatment outcomes is unknown. To determine the efficacy of pembrolizumab for platinum-refractory R/M-HNSCC, Cohen et al. conducted KEYNOTE-04018. The median OS was 8.4  months with pembrolizumab and 6.9  months with the physician’s choice of therapy , indicating an improvement in OS but still a poor outcome. Additional studies are warranted to compare outcomes between nivolumab and pembrolizumab as a first-line treatment for platinum-sensitive R/M-HNSCC.No prospective study has examined the effect of nivolumab in patients with platinum-sensitive head and neck cancer or with other carcinomas. The concept of platinum-resistant and platinum-sensitive cancer was originally used in the treatment of recurrent ovarian cancer and has recently been applied to R/M-HNSCC19. In our institution, we followed up with the patients every month after completing the local treatment for head and neck cancer and performed imaging studies every 3–4 months. In patients with suspected recurrence, imaging was performed at relatively short intervals. In this study, tumor burden and growth rate were not measured. However, R/M-HNSCC was likely diagnosed at a relatively early stage, resulting in the immediate administration of nivolumab. We believe this is one of the reasons for the favorable OS and PFS observed in this study. Unlike multicenter studies, our study did not require a specific time for the enrollment of patients, which enabled the rapid initiation of treatment, an advantage of single-arm studies conducted in a single institution.Suzuki et al. reported a reduced tumor growth rate after nivolumab treatment and found that the size of the target lesions affected OS and PFS as measured by the sum of their diameter20. They reported that patients without prior exposure were at a lower risk of death from nivolumab use. Cetuximab binds to the epidermal growth factor receptor on tumor cells but promotes the growth of immunosuppressive regulatory T cells in the tumor microenvironment21. Patients whose lesions worsen after cetuximab treatment are less likely to respond to immunotherapy owing to the proliferation of immunosuppressive regulatory T cells, such as regulatory T cells and myeloid-derived suppressor cells22. In our study, five patients (22.7%) with a history of cetuximab treatment before nivolumab treatment could not attain an endpoint for previous cetuximab use. Therefore, it is not known whether previous cetuximab use had any effect on patient response. The CheckMate-141 QOL assessments showed that nivolumab does not reduce the QOL (compared with other chemotherapy or molecularly targeted drug treatments)23. This observation is not limited to R/M-HNSCC; it has also been reported for melanoma, non-small cell lung cancer, and renal cell carcinoma26. Our results also showed no reduction in the QOL of patients after treatment with nivolumab.In a sub-analysis of data of CheckMate-141, Ferris et al. compared the OS of patients with and without prior exposure to cetuximabAmong the 22 patients, 16 irAEs occurred in 12 patients. Grade 3 or higher irAEs were liver dysfunction (N = 3) and hypothyroidism (N = 1). Nivolumab was discontinued due to irAEs in three patients with grade 3 liver dysfunction. After treatment with steroids, all patients showed an improvement in liver dysfunction. There were three other patients who discontinued nivolumab due to the deterioration of their general condition. Safety was not a significant problem.There were some limitations to the study. This was a single-arm study, and although the enrollment number was set at 50 patients, it was not reached. Sixty-one patients with R/M-HNSCC received nivolumab within the target period, but 35 were excluded due to platinum resistance. The effects of nivolumab in patients with platinum-resistant and platinum-sensitive R/M-HNSCC should be further examined in a multicenter prospective study with a higher number of patients. Therefore, as the next step of the study, we are investigating the results of treatment in platinum-sensitive and platinum-resistant groups in a multicentered study. The results of this study will be published separately. In addition, the outcomes of nivolumab and pembrolizumab as first-line treatments for patients with platinum-sensitive R/M-HNSCC with a history of platinum use should be compared in future studies. These studies are necessary to establish more effective treatment strategies for patients with R/M-HNSCC.In conclusion, our results suggest that nivolumab is highly effective in treating platinum-sensitive R/M-HNSCC, with no reduction in the QOL following treatment. These results may have implications for the current treatment regimen for R/M-HNSCC.This was a single-institution, open-label, single-arm, phase II interventional study conducted in Japan to evaluate the efficacy of nivolumab in patients with R/M-HNSCC. The study was approved by the ethics committee of Tokyo Medical University (SH3946) and registered at the University Hospital Medical Information Network Clinical Trials Registry prior to the recruitment of patients . The study adhered to the tenets of the Declaration of Helsinki, and informed consent was obtained from all the patients.Patients with R/M-HNSCC were screened for eligibility for this study. The number of patients expected to be enrolled was 50, which was calculated based on the number of patients with R/M-HNSCC treated in our institution (approximately 60 patients per year), the expected rate of enrollment (40%), and the study period to enroll patients (2 years). The main exclusion criteria were prior exposure to nivolumab; platinum refractoriness, defined as disease progression within 6 months after the last administration of platinum; non-squamous cell carcinoma; and age over 75 years. The complete inclusion and exclusion criteria are provided in the Supplementary Protocol.27. The QOL was assessed using the EORTC QLQ-C30, a basic quality of life questionnaire used for patients with malignancies, and the EORTC QLQ-H&N35, a disease-specific questionnaire29. The EORTC QLQ-C30 and QLQ-H&N35 were translated into Japanese and answered by the patients prior to treatment initiation and at 8 and 16 weeks after treatment initiation. These scores ranged from 0 to 100, with higher scores indicating higher functioning and symptom burden, except for the global health status items. Higher scores indicate lower functioning and symptom burden. TNM was classified using the Union for International Cancer Control stage, 7th edition30. The discontinuation criteria for nivolumab were specified in the protocol based on the grade of irAEs, but no weight loss criterion was set4. The irAEs were assessed using the Common Terminology Criteria for Adverse Events version 4.031.The primary endpoint was OS. The period of OS was defined as the duration between the date of nivolumab initiation and the date of the last follow-up or the patient’s death, whichever occurred first. The secondary endpoints were PFS, ORR, and QOL. The period of PFS was defined as the duration between the date of nivolumab initiation and the date of objective disease progression or patient’s death from any cause, whichever occurred first. Tumor response was assessed by three radiologists in our institution according to the Response Evaluation Criteria in Solid Tumors Guideline (version 1.1)32.Nivolumab was administered as a single intravenous dose (3 mg/kg body weight) every 2 weeks. A single treatment cycle lasted 2 weeks, and imaging assessment was carried out every 4–8 cycles. Treatment was continued until the confirmation of objective disease progression, the occurrence of unacceptable toxicity, or other reasons assessed by the attending physician. However, even after confirming progression based on clinical or imaging findings, treatment was continued when the attending physician thought that clinical benefit was likely32.PD-L1 was measured in CheckMate-141, and Dako 28–8 antibody  was used for immunohistochemical assay. The scoring systems include the Tumor Proportion Score (TPS), which measures PD-L1 on tumor cells, and the Combined Positive Score (CPS), which measures PD-L1 expressed on not only tumor cells but also macrophages and lymphocytes. In this study, the measurement was performed using the TPS, and not the CPS33. SPSS statistics version 22.0  was used for the statistical analysis of QOL. Results with P < 0.05 were considered statistically significant.OS and PFS were estimated using the Kaplan–Meier method. QOL assessments were conducted using a repeated measures linear mixed model, with repeated measures covariance structure as a composite symmetry, each QOL score as the dependent variable, time of measurement as a fixed factor, and subjects as a variable. In this case, the least squares mean and the 95% CI at each measurement point were calculated. The estimated mean and 95% CI were also calculated for changes based on the pre-nivolumab scores (baseline), and the significant change from the pre-nivolumab scores was tested. No correction for multiplicity was used. Statistical analysis for OS and PFS was performed using EZR, a statistical software that extends the functions of R and R commander; it is available on the Jichi Medical University Saitama Medical Center websiteSupplementary Information.


COVID-19 has stroke Brazil harshly, deaths by COVID-19 in Brazil represent almost 13% of the total deaths by COVID-19 in the world, even though Brazilian population represents only 2.6% of the world population. Our aim in this study was to evaluate death and intubation outcomes and risk factors associated with COVID-19, and treatment options focusing on diabetes patients and the use of metformin pre-admission and during hospitalization.In this Brazilian single-center study we evaluated 1170 patients hospitalized due to COVID-19. Diabetes patients (n = 188) were divided based on their use of pre-hospital and in-hospital metformin (non-met-group and met-group).In the total cohort most comorbidities were risk factors for orotracheal intubation and death. The use of chloroquine/hydroxychloroquine was significantly associated with increased death and intubation risk in uni- and multivariate analysis. Diabetes patients showed worst clinical feature compared with non-diabetes patients. In-hospital non-met-group had increased mortality (20.5%) compared to met-group (3.5%) (p = 0.0002) and univariable cox proportion hazard regression indicated in-hospital metformin reduced mortality . Patients that used pre-hospital metformin showed lower severity parameters at hospital admission. . In all the groups older patients showed more severe clinical conditions and high risk of death and intubation.Even though this is a single-center study, results from other reports have shown a similar trend, indicating that patients that used metformin during hospitalization have a better prognosis and reduced risk of death.The online version contains supplementary material available at 10.1186/s13098-021-00695-8. Deaths by COVID-19 in Brazil has reached the number of 501,825 on June, 21st 2021 (https://covid.saude.gov.br/).The COVID-19 pandemic is caused by SARS-CoV-2, a member of the Betacoronavirus genus of the Nidovirales order, its single stranded positive polarity RNA encodes non-structural and structural proteins, one important structural protein is the Spike, which mediates recognition of the ACE2 cell receptor. The non-structural proteins play pivotal role in cell regulation, that impacts host response to viral infection  for factors associated with the primary outcomes in-hospital mortality and orotracheal intubation, the results were not adjusted for multiple tests. Risk factors associated with in-hospital deaths were also assessed using a multivariable Cox proportional hazards regression model. Kaplan Meier method was used to compare the cumulative probability of in hospital death. The analyses were based on non-missing data. Statistical significance was defined as p < 0.05 and a two-side α was considered in the analysis. All statistical analyses were performed using IBM SPSS Statistics software version 25.0.Continuous variables were expressed as mean ± SD or median [max–min] and categorical variables as number and percentage (%). Differences between groups were analyzed using Student’s T-test, Mann–Whitney test, Kruskal Wallis Tests or ANOVA for continuous variables, and by ChiA total of 1,170 patients with COVID-19 were included in this study, 47.2% were women and 52.8% were males with mean age 51.8 ± SD 18.4. The most common comorbidities were hypertension (31.5%), diabetes (16.19%), dyslipidemia (14.6%) and obesity (10.4%). Among those patients 4.2% (n = 49) died during hospitalization. Univariable logistic regression showed that age and mainly, elderly of 60 years old or higher (≥ 60 group) was associated with high risk of in-hospital death  and with orotracheal intubation [OR 9.24 (2.22–38.51)] when compared with the 29–59 group. Considering the comorbidities, diabetes, cardiopathy hypertension, COPD/pneumonia, neurological disease, CKD and dyslipidemia were also death risk factors. All of the in-hospital clinical characteristics except the time of stay in nursery were associated with increased risk of death. Furthermore, all comorbidities, except asthma, and all clinical features, except time of mechanical ventilation and the use of prisma were risk factors associated with orotracheal intubation , as use of metformin was the focus and patients from both types have used metformin. The youngest patient of this group was 29 years old, thus for comparison, only patients over 29 years old (n = 895) were included in the non-diabetic group. The diabetic group showed higher frequency of men compared with non-diabetic (62.8% vs 51.3% p = 0.005), higher median age  and higher frequency of patients over 60 years old . All the comorbidities, except neurological disease, thyroid disease, neoplasia/immunosuppression, and all the in-hospital clinical characteristics, except the use of CHLO/HCQ, were significantly more frequent in diabetes patients when compared with non-diabetes. In agreement with these worse clinical features, the diabetes patients also had an increased mortality compared with non-diabetes (10.1% vs 3.4% p = 0.000) and almost all the dead patients of diabetic and non-diabetic groups were ≥ 60 years old . The ≥ 60 group showed high mortality , high rate of neurological disease; hypertension; cardiopathy, COPD/pneumonia), use of vasoactive drugs; orotracheal intubation and use of prisma. All smokers or former smokers were in the ≥ 60-group. This group showed higher scores of clinical severity at admission (NEWS), longer hospital stay and longer stay in ICU, longer time of in-hospital metformin and increased time of mechanical ventilation compared with 29–59 group . As metformin is an oral drug, orotracheal intubation interrupts the use of metformin. Therefore, considering only patients that did not needed orotracheal intubation during hospitalization, it was observed a tendency of increased number of deaths in the non-met patients compared with met-patients . Considering the comorbidities, the in-hospital metformin therapy was associated only with reduced hypertension and CKD. When the clinical characteristics were investigated, the metformin users only showed reduction in the in-hospital time of insulin therapy and frequency of patients that used prisma ; , respectively  . These patients also showed reduced cardiopathy, hypertension, COPD/pneumonia and neurological disease, and as expected most patients that received pre-hospital metformin also received in-hospital metformin 83.6% compared with 25% that did not receive metformin pre-hospitalization (p = 0.000)  vs 1.5 days (0–28) and 22 days (3–100) vs 9 days (4–47), p = 0.003]. Likewise, patients of the ≥ 60 group that received insulin had longer time of ICU and total hospitalization time compared to the group that did not received insulin ; . Patients under insulin therapy have a more pronounced disease severity.The univariable Cox proportional hazards regression model for in-hospital metformin therapy for diabetes patients was statistically significant  and the Kaplan Meier analysis also showed that the risk of mortality was reduced in diabetes patients that received pre-hospital or in-hospital metformin (log rank p = 0.01) ] and orotracheal intubations [OR 1.04 (1.01–1.07)], notably higher for diabetes patients over 60 years old, with an OR of [13.04 (1.701–99.96)] for mortality and [2.65 (1.22–5.79)] for intubation. COPD/pneumonia, smoking/former smoking, neurological disease and CKD were the comorbidities associated with the risk of dying, and COPD/pneumonia, smoking/former smoking and CKD associated with intubation. Considering the in-hospital clinical characteristics, NEWS, time of stay in ICU, time of MV, need for prisma, orotracheal intubation and use of vasoactive drugs were risk factors for death. Time of stay in nursery, pre-hospital metformin therapy and in-hospital metformin therapy were good prognosis factors, reducing death risk , respectively. Similar to the general group, the diabetes patients also had an increased orotracheal intubation and death risk after use of CHLO/HCQ ] and for intubation [OR 1.034 (1.001–1.07)], as well as cardiopathy was a death risk factor, while CKD was an orotracheal intubation risk factor. Considering the six drugs included in this study, vasoactive drugs and CHLO/HCQ were risk factors for both outcomes (death and intubation). When considered all the in-hospital clinical characteristics, the score of clinical severities at admission (NEWS) was a risk factor for mortality, while in-hospital metformin treatment reduced the risk of mortality  clearly indicate that all the patients suffering from the examined comorbidities, that presented worse clinical features at admission or that needed more invasive therapies had also increased chance for intubation and death risk. The rate of mortality in this cohort was 4.2%, similar to the non-diabetic group . However, in the diabetes patients it was higher (10.1%), as previously described . Most deIn this study age was a risk factor in univariate and multivariate analysis for mortality and orotracheal intubation in the complete cohort and in the diabetes patients. These results are in line with previous studies. Older age has been partially associated with the high frequency of multiple comorbidities  but it wAs in other study , our datIn our study the use of CHLO/HCQ during hospitalization was a risk factor for intubation and death in the univariate analysis for the cohort of 1770 and for the diabetic group. In the multivariate analysis considering the in-hospital procedures and drugs, the use of CHLO/HCQ was an independent risk factor for both outcomes in the entire cohort and the diabetic group. This is a relevant information, because there is a heated debate in Brazil over chloroquine use by COVID-19 patients.Chloroquine was proposed as an early repurposing drug against SARS-CoV-2, in vitro it has shown activity against MERS-CoV and SARS-CoV . AnalysiIt has been suggested that metformin use should be interrupted by COVID-19 patients , one of Our results in this study indicated that diabetes patients that used metformin prior to admission arrived with reduced clinical severity (NEWS) and suffered less with other comorbidities. Interestingly, those patients that used metformin before hospitalization and interrupted its use had increased mortality (21.1% vs 2.1%). A study of Spanish patients with diabetes mellitus type II (DM II) and COVID-19 indicated that metformin use at home had no effect in hospital death, mechanical ventilation or time of hospitalization . Data frConsidering the use of in-hospital metformin, the results of our study showed a significantly reduction of the mortality of diabetes patients with COVID-19 20.5% vs 3.5%). It is plausible to suppose that patients under metformin therapy were those with less severe diabetes and, thus, less at risk for severe Covid-19 infection. However, as shown in Table .5%. It iOne report observed a reduction in the incidence of ARDS in Chinese patients after taking metformin during hospitalization. The 30-day mortality was 3% and 11% in the metformin and non-metformin groups, respectively. However, no difference after propensity score matching was observed (HR = 0.48) . SeveralThe fact that metformin has an impact in survival of COVID-19 patients, but not in orotracheal intubation indicates that metformin potential activity against COVID-19 may not be related to inhibition of viral load or pulmonary insufficiency, but instead, metformin may prevent other life-threatening conditions, like exacerbated inflammatory response. In our study, the patients that received dexamethasone/prednisolone had increased survival when this therapy was combined with metformin. Proposed mechanisms of metformin in better prognosis of COVID-19 patients are improved glucose control, reduction in body weight and insulin resistance, inhibition of viral penetration due to phosphorylation of ACE2 by AMPK, inhibition of mTor, alteration of endosomal pH, reduction of neutrophils, ROS prevention, anti-inflammatory properties, inhibition of CRAC-mediated IL6 release , 43. PatAs a final remark is important to point some limitations of the study. It involves only one center, but it has a good test number subjects and statistical power. Still, not all drugs used by the patients pre- or in-hospital were listed, and despite our focus on metformin use one cannot exclude the influence of other treatments in the outcomes.In conclusion, in this Brazilian single-center study, the Santa Catarina Hospital—São Paulo, diabetes was an important risk factor for COVID-19 and diabetes patients that used metformin during hospitalization showed better prognosis and reduced risk of death, metformin improves dexamethasone/prednisolone survival of COVID-19 patients. On the other hand, patients that used CHLO/HCQ have increased risk of death. This study consolidates the potential of metformin against COVID-19, but more studies as a randomized controlled study with non-diabetes patients have to be conducted to properly address this subject.Additional file 1: Table S1. Comparison of demographic and clinical characteristics of diabetes and non-diabetic patients. Table S2. Clinical characteristics of diabetes’ patients compared by age. Table S3. Clinical characteristics of diabetes patients compared between dead and non-dead patients. Table S4. Univariate in-hospital risk factor associated with in-hospital mortality and orotracheal intubation of diabetes patients.


Resilience and well-being are strongly related. People with higher levels of well-being are more resilient after stressful life events or trauma and vice versa. Less is known about the underlying sources of overlap and causality between the constructs. In a sample of 11.304 twins and 2.572 siblings from the Netherlands Twin Register, we investigated the overlap and possible direction of causation between resilience (i.e. the absence of psychiatric symptoms despite negative life events) and well-being (i.e. satisfaction with life) using polygenic score (PGS) prediction, twin-sibling modelling, and the Mendelian Randomization Direction of Causality (MR-DoC) model. Longitudinal twin-sibling models showed significant phenotypic correlations between resilience and well-being (.41/.51 at time 1 and 2). Well-being PGS were predictive for both well-being and resilience, indicating that genetic factors influencing well-being also predict resilience. Twin-sibling modeling confirmed this genetic correlation (0.71) and showed a strong environmental correlation (0.93). In line with causality, both genetic (51%) and environmental (49%) factors contributed significantly to the covariance between resilience and well-being. Furthermore, the results of within-subject and MZ twin differences analyses were in line with bidirectional causality. Additionally, we used the MR-DoC model combining both molecular and twin data to test causality, while correcting for pleiotropy. We confirmed the causal effect from well-being to resilience, with the direct effect of well-being explaining 11% (T1) and 20% (T2) of the variance in resilience. Data limitations prevented us to test the directional effect from resilience to well-being with the MR-DoC model. To conclude, we showed a strong relation between well-being and resilience. A first attempt to quantify the direction of this relationship points towards a bidirectional causal effect. If replicated, the potential mutual effects can have implications for interventions to lower psychopathology vulnerability, as resilience and well-being are both negatively related to psychopathology. These adverse life event, but also events like terroristic attacks or worldwide crises, can lead to stress and trauma. There are individual differences in the responses of people to (major) life stressors and potential trauma , and resFor example, in response to the COVID-19 pandemic, only 13.6% of a USA representative sample (N = 1468) showed psychological distress . While tOne of the correlates of resilience that is often suggested to play a role in bouncing back to normal is well-being. Well-being can be defined in multiple ways and a distinction between subjective/hedonic and psychological/eudaimonic well-being has been made. The subjective well-being theory originates from the hedonistic philosophy of well-being, whereas psychological well-being emerged from eudaimonic philosophy . HedonicA strong positive correlation (around 0.5) between resilience and well-being has been found as well e.g. . That isAlternatively, underlying genetic or environmental confounders might induce the association between well-being and resilience - without a direct causal effect in either direction. The genetic and environmental factors contributing to both phenotypes have been investigated before. Two meta-analyses summarized all studies applying the twin model to well-being and found a meta-analytic heritability (i.e. the contribution of genetic factors to the variance) of 36% (CI: 34–38%) and 40% (CI: 38–43%) for well-being based on all measures  and 32% The above studies show that resilience and well-being are strongly related phenotypically and have a similar genetic architecture. The etiology of well-being and resilience has not been addressed in a bivariate design, to formally test the overlap in genetic and environmental factors. In order to get a better hold on the nature of the association between resilience and well-being, and possible roles for genetic confounding and  causal effects we took a three-step approach. (1) First, we estimated the cross-sectional and longitudinal phenotypic association between well-being and resilience. (2) Next, we used genome-wide summary statistics of well-being to predict resilience and well-being. (3) Finally, we tried to falsify the causal hypotheses (in both directions) using various approaches: within-subject change score regression, bivariate psychometric twin-sibling modeling, cross-trait correlations of intrapair MZ twin differences, and the MR-DoC model which combines Mendelian Randomization and the Direction of Causation twin model.22.1Participants were registered at the Netherlands Twin Register (NTR), established by the Department of Biological Psychology, Vrije Universiteit Amsterdam . The NTRIncluding twins and biological siblings, the total sample consisted of 14.055 participants with data on resilience and/or well-being collected in one or both waves. We excluded 177 participants with unknown zygosity and two participants with unknown sex, resulting in a final sample of 13.876 participants (11.304 twins and 2.572 siblings). The sample included 1.577 monozygotic male (MZM), 967 dizygotic male (DZM), 3.859 monozygotic female (MZF), 2.112 dizygotic female (DZF) and 2.789 dizygotic opposite-sex (DOS) twins from complete and incomplete twin pairs.Mage= 32.87, SDage = 11.41) had data at time point 1 (T1). At time point 2 (T2), data of 9.590 twins and 1.962 siblings  were available. Longitudinal data (both at T1 and T2) were available for 3.530 participants , 1 December 2008 and 2011/334, 12 Oct 2011; 2012/433, dd 26 Feb 2013).2.22.2.11 = strongly disagree to 7 = strongly agree. An example question is ‘In most ways my life is close to ideal’. Items were summed to calculate an individual's final score ranging from 0 to 35, with higher scores indicating higher levels of satisfaction with life.Well-being was assessed with the Satisfaction with Life scale . The sca2.2.2. In line with previous work, we excluded the positive life events at T2, leaving 19 items , 1–5 year ago and > 5 years ago. The number of life events was computed by summing the experienced life event in the past 5 years. The maximum number of life events experienced is 16 at T1 and 19 at T2  items of the scale, at T2s we only selected those same items and created a sum score of 15 items, with higher scores indicating higher levels of anxious-depressed behavior.Anxious-depressed symptoms were assessed with the anxious-depressed subscale of the Adult Self Report of the Achenbach System of Empirically Based Assessment ASEBA; . Each it2.2.4Resilience is operationalized as an outcome-based measure in line with To this end, the number of life events and the anxious-depressed scores were standardized. For both T1 and T2, the resilience score was operationalized as the residuals of the anxious-depressed sum score after the effect of the number of stressful life events had been regressed out, using Generalized estimating equation (GEE) to correct for familial relations . This st2.2.5Genotype and phenotype information was available for 10867 NTR participants in our sample. Genotyping was done on several genotyping arrays, including the Axiom array (N = 615), Affymetrix 6.0 (N = 6144), Illumina Omni Express 1 M (N = 181), Illumina 660 (N = 1312), Illumina GSA (N = 4044) and Perlegen/Affymetrix (N = 1013) see . Additio−5 were removed. Also, samples were excluded if there was a mismatch in expected and genotyped sex, the genotype missing rate was above 10% or the inbreeding value (Plink F statistic) was not between −0.10 and 0.10. To control for Dutch population stratification, Principal Components Analysis (PCA) was performed and individuals with a non-Dutch ancestry based on their PCs were excluded, as described by For each platform, SNPs with a Minor Allele Frequency (MAF) < 0.01 or SNPs out of Hardy–Weinberg Equilibrium (HWE) with p < 10−5, the Mendelian error rate was larger than the mean + 3 SD, or the imputation quality (R2) was below 0.90. The SNPs in the final cross-platform imputed dataset were aligned similarly to the 1000 Genomes Phase 3 v5 reference panel, and uploaded to the Michigan Imputation Server. Here, the data were phased and imputed to this 1000 genomes panel using Shapeit and Minimac3 respectively. The data were again filtered for SNPs having MAF <0.01, HWE p<10−5, alleles not being A, C, G, or T, and a call rate of 99% after all Mendel errors were removed. A random selection of 2500 s degree unrelated people were taken from this dataset. Using the summary statistics, this unrelated set and LDpred, the beta's were corrected. As described in more detail below, polygenic scores were constructed on the relevant 10867 individuals.To infer the SNPs missing per platform in the combined data, the genotyped data of the different arrays were cross-platform imputed using the GoNL as a reference panel . SNPs we2.32.3.1First, we applied a saturated twin-sibling model in OpenMx  includin2.3.2To investigate the molecular genetic overlap between resilience and well-being, we used summary statistics of two recent genome-wide association studies (GWASs) on resilience and well-being to create polygenic scores (PGS). PGS are a measure of an individual's genetic probability to develop a certain disorder or have a certain trait . Using GWe used PGS for resilience and well-being to investigate if and to what extent the genetic risk for well-being is a predictor for resilience and vice versa. For well-being, the polygenic scores from the most recent GWAS summary statistics for the well-being spectrum, leaving out NTR, were used . Using tThe polygenic scores were computed using LDpred . LDpred 2, sex, the genotyping array, and the first ten genomic principal components (PCs) as covariates. A significant association indicates that the genetic risk for resilience predicts well-being or vice versa. To correct for multiple testing, we used a Bonferroni corrected threshold of 0.001 for significance.Using GEE to correct for familial relations, we regressed the created PGS of resilience on well-being and vice versa and included age, age2.3.3Next, we investigated the possible direction of causation between resilience and well-being. Under the causal hypothesis, several predictions in cross-sectional and longitudinal data can be made , that ar2.3.3.1First, we used regression of the within-subject changes in well-being and resilience over time. If there is a causal relation from resilience to well-being, within-subject changes in resilience over time (T2 – T1) should predict parallel changes in well-being over time. Under the causal hypothesis, increases in resilience over time would result in increase in well-being. The absence of a correlation of change scores over time would reject the causal hypothesis, whereas the presence of a correlation is in line with causality . Using G2.3.3.2Another prediction under the causal hypothesis is that if resilience is causally related to well-being, all genetic and environmental factors that influence resilience will also, through the causal chain, influence well-being .To test the significance of genetic and environmental correlations between resilience and well-being, we used twin-sibling models. Bivariate twin-sibling models use the difference in genetic overlap between monozygotic (MZ) twins and dizygotic twins (DZ) to estimate the underlying sources of phenotypic variance of two traits and their phenotypic correlation. In addition, these model results can be used to calculate genetic and environmental correlations . MZ twin2 distribution with the degrees of freedom (df) equaling the difference in df between two models. If a p-value from the χ2 -test was higher than the alpha of 0.001 (corrected for multiple testing), the constrained and more parsimonious model fit was not significantly worse than the fit of the more complex model. The distribution of resilience and well-being scores were moderately skewed, but showed a bell-shaped curve and were therefore analyzed as continuous variables. Furthermore, whereas the skewed data might bias the parameter estimates, transformations do not remove the known and small bias , the full ACE/ADE models were compared to nested submodels. The difference in minus two times the log-likelihood (-2LL) between two nested models has a χl effect ).As we have data on resilience and well-being at two time points, we modelled the variance of the underlying phenotypes in a bivariate psychometric model with repeated measures. The resilience and well-being scores at T1 and T2 can be seen as an index of the true measure including measurement error . For botTo investigate the overlap and genetic architecture of the latent factors of resilience and well-being, we estimated genetic and environmental contributions to the variance and covariance of the latent factors. Furthermore, the genetic and environmental correlations are calculated. In this model, we first tested for quantitative sex differences  by constraining the estimates of A, C/D and E to be equal in males and females. Next, we estimated the contribution of the variance components A and C/D to the total variance and covariance of the phenotypes. We did not test for qualitative sex differences, as modelling sex specific genes in multivariate models has inherent limitations  and no qIf resilience and well-being are causally related, genetic and environmental factors influencing individual differences in one trait will, through the causal chain, also influence individual differences in the other trait. To test this causal effect hypothesis, we tested the genetic or environmental correlation between the latent traits in the bivariate model. Both the genetic and environmental correlation should be significant if there is causality. A significant genetic correlation but a non-significant environmental correlation falsifies the causal hypothesis and a common genetic factor is then more likely to underlie the association between resilience and well-being.2.3.3.3In a similar way, we can use the longitudinal data of resilience and well-being in a bivariate model . If resi2.3.3.4twin 1 – Resilience twin 2) in resilience should be associated with within-twin pair differences in well-being (Well-being twin 1 – Well-being twin 2) and vice versa. The twin who is more resilient should have a higher well-being score than the co-twin who is less resilient. At both time points, we regressed the MZ intra pair differences in resilience on the difference in well-being and vice versa. Since monozygotic twins are genetically identical, this test excludes confounding by genetic and shared environmental factors. However, if there is an association, also other factors in the non-shared environment of the twins can underlie this association.Another prediction made by the causal hypothesis is that the within–twin pair differences of genetically identical (MZ) twins in resilience should be associated with within–twin pair differences in well-being. We applied the monozygotic within-twin pair differences method. If there is a causal relation, the MZ twin differences  in resilience over time are associated with intrapair differences in individuals’ changes in well-being over time and vice versa. Again, significant associations are in line with a causal hypothesis. The twin who has a larger increase in resilience should have a larger increase in well-being than the co-twin who showed less increase in resilience. To test this association, we created within-individual change scores of resilience and well-being and the difference between these change scores of MZ twin pairs. We regressed the MZ intra pair differences in resilience on the difference in well-being and vice versa.2.3.3.5To explicitly test causality, allowing for coexisting genetic confounding, we leveraged the unique database of the Netherlands Twin Register and applied the Mendelian Randomization- Direction of Causation (MR-DoC) model. The MR-DoC model uses twin data and polygenic scores, combining the strengths of Mendelian Randomization and the Direction of Causation twin model . In Fig.In the traditional direction of causation twin (DoC) models , the covIn Mendelian Randomization, genetic variants are used to test causal relationships between an exposure variable and outcome . The genPleiotropy can be divided into direct pleiotropy . Using the cross-twin cross-trait correlations of MZ and DZ twins (like in the standard DoC model), the causal path (g1) between the traits can be estimated. At the same time, using the polygenic score, the MR part of the model normally estimates the causal effect from b1 and the observed covariance between PRS and the outcome trait (using covariance = g1*b1), assuming pleiotropy to be absent (path b2 = 0). As g1 is estimated from the twin DoC part, combining the covariance structure and effect of the PGS on the outcome trait, pleiotropy (path b2) can now be directly estimated. Moreover, when estimating the causal effect in the twin DoC part, pleiotropy is accounted for , as is often the case, but problematic for the DoC part of the model see , the env1) is larger than zero, there is a causal effect from well-being to resilience. The b2 estimate reflects the pleiotropy between well-being and resilience. Based on the results, the effect size (% variance) of the directional effect can be estimated, taking into account the presence of residual genetic pleiotropy.We tested whether well-being causally affects resilience using the well-being PGS, the exposure being the well-being score and the outcome being the resilience score at time point T1 and T2 separately. If the estimate for the causal effect from well-being to resilience  and T2 . The residuals from the GEE models were used as the measure for resilience.The definition of the resilience assumes a positive association between stressful life events and anxious-depression and variability in the anxious-depressed score after stressful life events. Consistent with this definition, people differ in their response to stressful life events, i.e. the variance around the point estimate of anxious-depressed score increased when the number of life events experienced increased see . The num3.2In a saturated twin-sibling model, the mean score for well-being could be constrained to be equal across males and females, (p = .113). For resilience, the means could not be constrained to be equal across sexes (p < .001). The resilience score for men was significantly higher compared to women, indicating that on average men are more resilient than women. The descriptives are given in 2  on well-being in both waves. Similarly, there is a small effect of age and age2  on the resilience score. This reflects a U-shaped curve for both well-being and resilience, indicating that younger and older people score higher on resilience and well-being than people in middle adulthood.There is a small, but significant effect of age  and age3.3The polygenic score predictions of resilience and well-being using the different fractions of included SNPs (1–0.01) are in The well-being PGS is a significant predictor for both well-being and resilience at both time points (p < .001), explaining around 0.8–0.9% of the variance in well-being and 1.4–1.8% of the variance in resilience , SE = 0.02, Z = 15.67, p < .001. Similarly, within individual change in well-being predict a parallel change in resilience over time, β = 0.34 (95% CI: 0.30 −0.38), SE = 0.02, Z = 15.95, p < .001 see . These r3.4.2The full bivariate ADE measurement model with sex differences is shown in In the final bivariate model, the heritability of the latent well-being factor is estimated at 54.8% (95% CI: 53.1–57.1), whereas the unique environment explains 45.2% (43.1–51.4) of the variance in well-being. The heritability of the latent resilience factor is 60.9% (95% CI: 60.6–62.3) and the unique environment explains 39.1% (38.9–41.2) of the variance. At time 1 and time 2, time specific genetic influences explained respectively 32% and 37% of the variance in well-being in females. For males, the time specific heritability of well-being was similar, with 32% and 35% at T1 and T2 respectively. For resilience, the time specific heritability was 45% and 43% for females, but lower for males, with 39% and 36% at T1 and T2 respectively.Of the covariance between resilience and well-being, 51.2% is explained by genetic factors and 48.8% by environmental factors. The genetic and environmental correlation between the latent factors of resilience and well-being are 0.71 (95% CI: 0.70-0.71) and 0.93 (95% CI: 0.86-0.98) respectively. As expected under the causal model, the genetic and environmental correlations could not be constrained to zero, p < .001 see .3.4.3In a bivariate longitudinal twin model with the resilience score at T1 and well-being at T2, we could not constrain the estimates to be equal across sex. Thus we tested the significance of the genetic and environmental correlations separately for males and females, by constraining the covariance between resilience and well-being. In line with the measurement model, we dropped D dropped (p = .005). The genetic correlations from resilience at baseline and well-being at T2 were 0.62 (95% CI: 0.53-0.74) and 0.63 (95% CI:.41-0.85) for females and males respectively. The environmental correlations were 0.19 (95% CI:.11-0.26) and 0.23 (95% CI:.10-0.35). Constraining any of the correlations to zero resulted in a deterioration in fit (p < .001) see , in lineIn a bivariate model with the well-being score at T1 and resilience at T2 separately for males and females, we dropped D (p = .002). The genetic correlation from well-being at baseline and resilience a few years later were 0.64 (95% CI: 0.52-0.76) and 0.29 (95% CI: 0.24-0.55) for females and males respectively. The environmental correlations were 0.20 (95% CI: 0.12-0.27) and 0.32 (95% CI: 0.19-0.43). Constraining the genetic correlation to zero in females or the environmental correlation to zero in males and females resulted in a deterioration of the model fit (p < .001). In males, constraining the genetic correlation to zero did not change the model fit (p = .033) see  which se3.4.42 = 0.15, p < .001, T2: β = 0.47, SE = 0.02, R2 = 0.21, p < .001). Similarly, regressing the well-being difference score of MZ pairs on the resilience difference score resulted in significant estimates   in the model, as both well-being resilience are AE traits. However, we can fix the rE to a correlation of various sizes instead of fixing the correlation to zero. As exploratory analyses we ran different MR-DoC models fixing the rE to respectively 0.1, 0.2, 0.3, 0.4, 0.5, and 0.8 at both time points , but no sex difference in the genetic architecture of the latent factors for resilience and well-being. Results based on studies using GWAS summary statistics provided weak support for causal effects. Polygenic score analyses showed that the genetic risk for well-being is a predictor for resilience, but the genetic risk for self-reported resilience did not predict indirect resilience or well-being. The results of different causality analyses in twin-sibling models  were notUsing a psychometric twin model with data of two time points, the heritability estimates for the latent traits well-being and resilience were similar with respectively 54.8% and 60.9%. More than half of the variance in the stable part of resilience and well-being is explained by genetic factors. Whereas the heritability estimates at the two time points were around 30–40% for both traits, the heritability estimates of the psychometric model were higher, as this is not confounded by measurement error and time-specific influences. These estimates are highly comparable to earlier studies on resilience and well-being .About 50% of the covariance between resilience and well-being is explained by genetic factors and the strong genetic correlation (0.71) indicates that the genetic factors underlying resilience and well-being overlap significantly. Environmental factors explain the other half of the covariance between resilience and well-being. The environmental correlation between the latent traits is close to unity (.93) and indicates an almost perfect overlap in the environmental factors influencing both traits.The various analyses using genetically informative samples were not successful in falsifying the causal hypothesis, even when correcting for genetic confounding. Therefore, we suggest that our findings are in line with a bidirectional causal relation between resilience and well-being instead of an underlying set of genes and/or environmental factors. To strengthen this finding, we applied the MR-DoC model. The MR-DoC model allows us to estimate causal effects, even in the presence of pleiotropy between the phenotypes. This model yielded results consistent with a causal relation from well-being to resilience, with about 11% (T1) and 20% (T2) of the variance in resilience explained by a causal effect from well-being. Due to the limited power of the resilience PGS, the causality in the other direction, from resilience to well-being could not be tested reliably in the MR-DoC model.The assumption that the unique environmental sources of variation for resilience and well-being equals zero is necessary in the MR-DoC model for identification and this might seem implausible as we find an environmental correlation of 0.93 for well-being and resilience in the latent twin-sibling model. However, the unique environmental effects on well-being can be related with resilience via the causal path only, where the unique environmental effects influence the outcome via its effect on the exposure and not directly. In bivariate twin models, this causal path is missing, what could result in a large environmental correlation.As exploratory analyses, we fixed the environmental correlation to various sizes instead of fixing the correlation to zero. This led to equal model fits for an environmental correlation of 0, 0.1, 0.2 and 0.3, as we did not have the power to distinguish between these models. At time point 1, the estimate of the causal effect from well-being to resilience decreased from 11.6% when the environmental is zero to respectively 6.6%, 3.0% and 0.7% with a rE of 0.1, 0.2 and 0.3. With a higher environmental correlation, the model fit started to decrease and the causal effect estimate was not significant anymore. These results indicate that the model does find a causal effect between well-being and resilience. However, it is likely that there is an environmental correlation between well-being and resilience as well, reducing the size of the causal effect. More power is needed to determine the size of the causal effect.Another explanation for the strong correlations between resilience and well-being could be a third variable underlying both traits and explaining the bidirectional relationship between them. For example, self-rated general health has a strong genetic correlation with well-being , althoug4.24.2.1There is discussion about definition of resilience and well-being resulting in no universal or commonly agreed upon definition. Different questionnaires are validated to assess self-report resilience, like the Ego-Resilience scale  and ConnWe defined resilience as the better than predicted psychological outcome based on the number of stressful life events experienced. A difficulty in this definition is the inclusion of the type and number of life events experienced. In our study, we included 16 and 19 (time 1 and 2) life events about illness, dead of close others and events like robbery and accidents. This is not an exhaustive list of life events and the personal impact of life events might differ per individual. Furthermore, treating all these different types of stressful events as equivalent is not likely to be true. Therefore, further research should weight the personal impact of life events or group the life events in different categories to better operationalize resilience and to get a better hold on the direction of causation between resilience and wellbeing.Furthermore, whereas we focused on the absence of psychopathological symptoms after stress as our resilience measure to compare the overlap with well-being, another approach to measure resilience is to assess the positive adaptation after stress  resilience . The GWAAs can be seen in our results, the power to detect association between the resilience PGS and the resilience measure was low. The resilience PGS did predict indirect resilience to some extent, but the variance explained was almost zero (<0.001%). Furthermore, although there is an indication for a genetic relation and overlap between resilience and well-being, the self-reported resilience PGS did not predict well-being. Due to the low power of the resilience PGS and the small association between the resilience PGS and resilience score, applying the MR-DoC model including the resilience PGS would not lead to reliable results. Not all MR assumptions (i.e. the strong association between the genetic instrument and exposure) are fully met.The MR-DoC model can be extended to test a bidirectional relationship, including both PGS of resilience and well-being at the same time. Such a model can strengthen the results and the constraint of the environmental correlation to zero is not necessary anymore. However, for this model two sets of powerful polygenic scores are needed. As the resilience PGS lacks power, we did not model such a bidirectional MR-DoC model. Similarly, as the resilience GWAS is not predictive of our outcome-based measure of resilience and did not have much power, we did not apply SNP based MR methods, such as two-sample MR methods, like MR-Egger. Even if these methods would show causality, the results will not be informative about the relation between well-being and outcome-based resilience, as it has been shown that there is only a moderate degree of genetic overlap between self-reported and outcome-based resilience, using twin models .The less powerful PGS for resilience due to the small GWAS discovery sample and different operationalization of resilience limits the interpretation of the molecular genetic analyses in our study. To replicate and strengthen our findings on the overlap and direction of effect between resilience and well-being with molecular genetic data, a powerful GWAS for resilience as response to stress (instead of direct self-reported resilience) carried out in a large sample from the general population is needed. In line with our operationalization, a measure of internalizing problems (e.g. anxiety and/or depression) and the number of experienced life events can be combined to create such a measure of resilience in a large genotyped sample.https://pan.ukbb.broadinstitute.org/).Lastly, as with most GWASs, we used the summary statistics resulting from studies restricted to individuals with European ancestry. Therefore, our results might not generalize to populations of different genetic ancestries. Recently, large projects to include individuals from other ancestries have been started as analyzing a more inclusive and diverse dataset might increase power to detect associations  can protect an individual's well-being after stress. The independent interventions related to increasing well-being and separate interventions for coping with trauma might supplement each other.The results in our large genetically informative sample suggest a large overlap and a potential bidirectional relationship between resilience  and well-being (life satisfaction). If replicated, the results implicate that increasing well-being might lead to increased resilience  as well and vice versa. As resilience and well-being are both negatively related to psychopathology , the bi-ERC consolidation grant , NWO large investment grant (NTR: 480-15-001/674)) and ZonMW Addiction program (31160008).This work is supported by an Lianne P. de Vries: Conceptualization, Methodology, Formal analysis, Writing – original draft, Visualization. Bart M.L. Baselmans: Methodology, Writing – review & editing. Jurjen J. Luykx: Writing – review & editing. Eveline L. de Zeeuw: Writing – review & editing. Camelia C. Minică: Methodology, Writing – review & editing. Eco J.C. de Geus: Methodology, Writing – review & editing. Christiaan H. Vinkers: Conceptualization, Writing – review & editing, Supervision. Meike Bartels: Conceptualization, Methodology, Writing – review & editing, Supervision, Funding acquisition.Lianne de Vries, Bart Baselmans, Jurjen Luykx, Eveline de Zeeuw, Camelia Minica, Eco de Geus, Christiaan Vinkers and Meike Bartels declare no conflict of interest.


The analytical performances of the proposed RNA aptasensor were better than the previously reported aptasensors for CRP. The proposed aptasensor was also applied for the determination of CRP in the human plasma samples. The obtained results indicated that there were no statistically significant differences between the responses of the proposed RNA aptasensor and an enzyme-linked immunosorbent assay kit (ELISA). The analytical performances of the proposed RNA aptasensor described in this paper are better than previously reported aptasensors for CRP determination.C-reactive protein (CRP) is one of the biomarkers related to coronavirus disease 2019 (COVID-19). Therefore, it is crucial to develop a highly sensitive, selective, and cost-effective biosensor for the determination of CRP. In this study, we designed an electrochemical aptasensor. For this purpose, the surface of a carbon screen-printed electrode was first modified with a carbon nanofiber-chitosan (CNFs-CHIT) nanocomposite. After that, the amino-terminal RNA aptamer probes were linked to the amino groups of CHIT via glutaraldehyde as the cross-linker. Finally, methylene blue (MB) as a redox probe was self-assembled on the surface of the aptasensor. The obtained results indicated that the CNFs-CHIT nanocomposite increased the surface coverage of the aptamer up to 5.9 times. The square-wave voltammetry was used for the measurement of CRP concentration in the linear range of 1.0–150.0 pM. The obtained results indicated that the signal had a logarithmic relationship with the concentration of CRP. The limit of detection (LOD) was obtained to be 0.37 pM. The dissociation constant (K Sepsisis a potentially fatal response of the body to an infection that can lead to death in the framework of many diseases like coronavirus disease 2019 (COVID-19) . Th. ThMB) wol cm−2) . TherefoFaradic) was obtained for the anodic peak current of the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB. As shown, the total charge QTotal includes the non-Faradic and Faradic charge:Non-Faradic) from QTotal (the charge below the red area), the QFaradic can be obtained  on the modified electrode was also investigated. Since every CRP aptamer probe sequence contains 44 phosphodiester groups and a phosphodiester group interacts with an MB, the ΓMB can be converted to ΓAptamer [A is Avogadro’s number (6.022 × 1023 molecules mol−1). The aptamer surface coverage ) or 1.35 × 1013 molecules cm−2 (by using Equation (6)),which was greater than previously reported for the CRP aptamer probe [Aptamer on the CSPE/CHIT-GLU-RNA aptamer-MB was also obtained with the same method used for the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB , respectively. The value of Γer probe . The valtamer-MB –C. The vAptamer value up to 5.9 times.s) for MB was also calculated for the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB using Laviron’s formula for the surface controlled electrochemical system  [−1), F is the Faraday constant , R is the universal gas constant (8.31 J K−1 mol−1), and T is the temperature (298 Kelvin). The average value of Ks for MB was found to be 1.83 s−1, suggesting that the electron transfer of the self-assembled MB on the proposed aptasensor has good reversibility.The heterogeneous electron transfer rate constant (Kα = 0.5) . This isThe influence of the volume of the CNFs-CHIT (A), the concentration of the immobilized RNA aptamer on the amount of the self-assembled MB (B), and the incubation time on the response of the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB to 20.0 pM CRP (C) were investigated  by usingAs can be seen in The effect of the incubation time was also studied C. As canCRP) decreased logarithmically as the CCRP increased from 1.0 to 150.0 pM (The SWV method was applied for the measurement of the various concentrations of CRP A. As sho150.0 pM B. The co−1 cm−2. The limit of detection (LOD) was found to be 0.37 pM (3σ/S), where σ is the standard deviation of the blank measurements for four different aptasensors  and S the slope of The sensitivity was 9.0 μA pML), the dissociation constant (Kd), and the maximum number of binding sites (Imax) for the CRP-RNA aptamer were also obtained using the Langmuir adsorption systems equation [The value of the Langmuir isotherm constant (Kequation . Equatiomax and 1/KL × Imax can be obtained from the slope (0.043) and intercept point (−0.04) in max, KL, and Kd (1/KL) were found to be 23.25 µA, 1.07 pM−1, and 0.93 pM, respectively. The value of Kd is lower than the previously reported RNA aptasensor for CRP [The values of 1/I for CRP , indicat−1 [−1 mol−1, and T is the temperature (298.15 Kelvin).Moreover, the Gibbs free energy for the desorption band of the CRP-RNA aptamer was found to be −179.6 kJ mol−1 . This isThe analytical performance of the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB was compared with other aptasensors for CRP measurement . It is oThe selectivity of the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB was also studied . As can The reproducibility of the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB was evaluated by three newly fabricated aptasensors . The relHuman serum samples were prepared based on the previous report. Details are included in the supplementary data section. Serum samples 40.0 μL in amount were added to 156.0 µL PBS and mixed for 15 min. Then the solution was divided into two samples. After that, 2 µL CRP solution with different concentrations  was added to each of the two solutions and mixed for 15 min. The CRP concentration was 2.0 pM for the first diluted serum sample and 10.0 pM for the second one. The CRP concentration in the real sample was calculated by using the calibration curve B. FigureWhile the CSPE/CNFs-CHIT-GLU-RNA aptamer-MB demonstrated excellent analytical performance in terms of sensitivity, stability, and selectivity, its response time is slower than the immunosensors. Therefore, our future plans include designing a new aptamer probe to decrease the response time of the sensor.In this study, an electrochemical RNA aptasensor was introduced with a strategy based on the association of the CNFs, CHIT, and MB to measure CRP concentration. The investigations indicated that the CNFs-CHIT nanocomposite increased the aptamer surface coverage dramatically. The proposed RNA aptasensor for the CRP measurement had a wider linear-response range and a lower LOD, and an affinity. The obtained results also demonstrated that the proposed RNA aptasensor has good stability, reproducibility, and selectivity. Moreover, there were not any significant differences between the responses of the proposed RNA aptasensor and a CRP-ELISA kit in human serum samples. The analytical performances of the proposed RNA aptasensor were not only better than the aptasensors previously reported for CRP, but also better than the immunosensors previously reported for CRP . This is


Anopheles mosquitoes to Plasmodium invasion has been extensively studied and shown to be mediated mainly by the nitric oxide synthase (NOS), dual oxidase (DUOX), phenoloxidase (PO), and antimicrobial peptides activity. Here, we studied the correlation between a heat shock insult, transcription of immune response genes, and subsequent susceptibility to Plasmodium berghei infection in Anopheles albimanus. We found that transcript levels of many immune genes were drastically affected by the thermal stress, either positively or negatively. Furthermore, the transcription of genes associated with modifications of nucleic acid methylation was affected, suggesting an increment in both DNA and RNA methylation. The heat shock increased PO and NOS activity in the hemolymph, as well as the transcription of several immune genes. As consequence, we observed that heat shock increased the resistance of mosquitoes to Plasmodium invasion. The data provided here could help the understanding of infection transmission under the ever more common heat waves.The immune response of  These transcriptional factors control the expression of hundreds of genes, including many immune response genes. The immune response has been shown to be intertwined with the general stress response in several insect models, and a number of genes activated by pathogen invasion are not directly linked to anti-pathogenic functions. For instance, LPS injection of the Tribolium castaneum beetle also induces heat shock stress response genes (HSP 68 and HSP 27) and hypoxia-inducible gene transcription  expression peaked at 30°C, the humoral melanization, phagocytosis, and defensin expression were maximum at 18°C    (kindly in (GFP) . Groups Drosophila HSF binding reaches a maximum level following a 30-minute heat shock at 36.5°C ). The resulting solution was cleared by 15 min centrifugation at 14,000y et al. . SamplesSome 25 μg of mosquito protein extract were separated in SDS-PAGE (10% acrylamide) and transferred to Immobilon-P membrane. The protein transfer on the membrane was assessed by Ponceau S (P7170 Sigma-Aldrich) staining. For the Hsp-70 immunodetection, anti-Hsp70 monoclonal antibody [3A3] Thermo Scientific MA3-006 was used as primary antibody at a final dilution of 1:1,000, and goat anti-mouse-IgG-horseradish peroxidase (Abcam) diluted 1:1,000 as secondary antibody. Development of immunoblots was performed with an ECL kit from Amersham. Fluorescence was developed on a Kodak BioMax ML-2 film for capturing chemiluminescent data  using Kodak Developer  and Kodak Fixer .P. berghei infection (30-hours post-heat shock) as described elsewhere (Hemolymph was obtained by perfusion from 30 control and heat-shocked mosquitoes (at six hours post-heat shock), and 24-hours post-lsewhere . Three eTotal RNA from 10 whole female mosquitoes (without head) and midguts only, were obtained by Trizol method (Invitrogen) and then re-purified using RNA Clean-Up Kit (Zimo Research). cDNA was synthesized by reverse transcription using 1 µg of RNA, 100 ng of oligonucleotide dT, and 200 U of the enzyme reverse transcriptase RNase H-SuperScript II (Gibco BRL). Three experimental repetitions were performed, each counting three samples per conditions.An. albimanus immune response was carried out with previously recovered genetic material. Specific primers were used for each gene  under optimal running conditions, according to the manufacturer’s recommendations. Samples were incubated at 60°C in a master mix containing SYBR Green , primers, and cDNA of each of the samples, set to a volume of 20 μl with water free of nucleases (Thermo Scientific). The relative expression was quantified by normalizing the expression of immune response genes with the S7 ribosomal gene.Assays were performed three times in different batches of 10 mosquitoes and three times in different batches of five mosquitoes’ midguts. The control and experimental tests were made at the same time. For real-time PCR, 2.5 µl of cDNA was used in SYBR Green I Kit (Applied Biosystems) following the kit instructions. The primers used are described in g for 10 min at 4°C. L-DOPA was used as the substrate for PO, which is transformed into the dye dopachrome. Auto-oxidation controls (L-DOPA only) and blanks (macerated mosquitoes) were included. PO activity was measured every minute for 30 min at 490 nm in a microplate reader .PO activity was measured as described . Three pg for 10 min at 4°C. Proteins were eliminated with ZnSO4. Nitrates were reduced into nitrites using VCl3 immediately followed by the addition of sulfanilamide and NED. The reaction was incubated for 15 min at R.T., and the absorbance was measured at 490 and 630 nm in a microplate reader.Nitrites ss assay . Pools oData were analyzed and graphed in Prism v6.01 statistical software. qPCR results were evaluated by one way ANOVA followed Tukey’s test (Whole body RT-qPCR), and unpaired t test with Welch’s correction (Midgut RT-qPCR). The infection parameters were analyzed through Mann–Whitney. Considering that three independent repetitions of the experiment were performed, we applied a log-like generalized lineal model with random effect to determine the difference in ookinete prevalence between control and heat shocked mosquitoes. We used the individual experimental repetitions as categorical variable, this with the objective of measuring the effect of the individual repetitions on the mean differences between the two conditions. PO and NO results were analysed by Student’s t-test comparing the heat shock and control groups for the non-infected and infected mosquitoes.A. albimanus (susceptible strain) mosquitoes were heat-shocked at 37°C for half an hour, 6 h before infective blood-feeding (900 ookinetes/µl) in three separate experiments with three replicates. Oocyst numbers were assessed five days post blood meal. The prevalence and the intensity were significantly diminished in the heat-shocked mosquitoes . A median of three oocyst per mosquito midgut were found in control mosquitoes while a median of two oocysts per midgut were found in the heat shocked mosquitoes midguts . Samples were tested for phenoloxidase activity using the colorimetric L-DOPA assay. As can be seen in P. berghei infection increased hemolymph phenoloxidase activity, mainly through enzymatic activation by proteolysis and secretion of prophenoloxidase. While heat shock alone did not increase hemolymph phenoloxidase activity, heat shock increased the hemolymph phenoloxidase activity  showed the largest effect. In summary, heat shock alters the expression of many genes and induces the activation of phenoloxidase enzyme as well as increasing transcription of its gene. Infection also increased the activation of phenoloxidase.Stress history drastically influences the mosquito immune system. The response to heat shock is generally characterized by heat shock protein expression. This response is, in the case of nfection . The expntiation , 41. In exposure . In this berghei . In Tribgramming . In insetibility . Here, wobserved Figure 6P. berghei infection without requiring a prerequisite bacterial immune challenge as reported by Dieme et al.  can be found in the article/RC and HL-M conceived the presented idea. RC developed the theory and performed the statistics. EH-T, FC-P, BR-T, KM-M, and VC-J carried out the experiments. RC and HL-M wrote the manuscript with support from BR-T and FC-P. FC-P, KM-M, and VC-J fabricated the mosquito samples. EH-T, FC-P, BR-T, KM-M, and VC-J processed and analyzed the samples. HL-M supervised the project and planned the experiments. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.